With development of computer technologies, human behavior identification is a field that continuously develops in computer vision, and particularly develops with the big data era. Recently, an increasing quantity of studies focus on group behavior identification, for example, supervised learning behavior identification for a feature-based covariance matrix, which has a powerful anti-mutation behavior, viewpoint switching, and a low resolution, and for another example, a behavior that simulates a complex time space interaction by using an interval Bayesian network, an original motion event of unsupervised grouping and one-time learning that are based on a unified framework of human behavior, posture, and facial expression, and the like. The foregoing behavior analyses are all applied to analyzing a large quantity of behaviors of an individual or a group.
Due to variations of light, posture, and occlusion, hand motions cannot be accurately identified.